Accurately analyzing internal conditions of a furnace is an essential task for an operator to better control temperatures of different regions in a furnace enclosure for producing products more efficiently and saving energy-related costs. Typically, image-capturing devices, such as color cameras, infrared spectrometers, filtered cameras, and the like, are installed in the furnace enclosure for detecting the temperatures of the furnace enclosure. Intensities of image pixels received from the devices have a direct relationship with the temperatures of viewed surfaces inside the furnace. Similarly, multi-spectral cameras have been used to detect the temperature of a flame and gas species.
A certain method of video-based technology provides color or intensity images to the operator allowing the operator to manually interpret the state of the combustion process based on the images. Another technology performs off-line intensity-temperature calibration and maps each color image to a specific temperature image, thereby providing a two-dimensional (2D) projection of the temperature and/or radiance field. Other technologies, such as laser, and acoustic, offer three-dimensional (3D) temperature and/or radiance field estimation at specific locations inside the furnace enclosure. However, a number of required sensors, a related cost, and a complicated installation often make such systems impractical in a large scale enclosure.
Another technology for video-based, three-dimensional temperature and/or radiance field estimation applies thermal radiation transfer equations to the temperature images. However, this method is inefficient and inaccurate, and does not provide a required resolution and accuracy due to complex, iterative computations required to resolve unknown temperature and radiance fields in the enclosure. Another reason for the inaccuracy is attributed to poor-quality images caused by incorrect or limited controls of the image-capturing devices. Achieving an acceptable accuracy in high resolution and accurate alignment of the images along with information about a physical structure of the enclosure is essential. As discussed above, relative positions of the image-capturing devices and imaging areas, such as enclosure walls, often shift their alignments and thus cause significant errors.
A certain method uses multi-spectral imaging technology for the detection of the gas composition in an open environment. This method only detects the presence or absence of certain gases along a viewing path, but cannot provide the distribution of gas species in a three dimension field.
Therefore, there is a need for an improved method of estimating and detecting temperature and radiance fields of the enclosure without generating substantial errors or variations during the combustion process of the furnace. Further, the estimation of gas species field provides the operator a better tool to improve the efficiency of the furnace enclosure.